Matches in SemOpenAlex for { <https://semopenalex.org/work/W3100194670> ?p ?o ?g. }
Showing items 1 to 97 of
97
with 100 items per page.
- W3100194670 endingPage "P08020" @default.
- W3100194670 startingPage "P08020" @default.
- W3100194670 abstract "Data analysis in high energy physics often deals with data samples consisting of a mixture of signal and background events. The sPlot technique is a common method to subtract the contribution of the background by assigning weights to events. Part of the weights are by design negative. Negative weights lead to the divergence of some machine learning algorithms training due to absence of the lower bound in the loss function. In this paper we propose a mathematically rigorous way to train machine learning algorithms on data samples with background described by sPlot to obtain signal probabilities conditioned on observables, without encountering negative event weight at all. This allows usage of any out-of-the-box machine learning methods on such data." @default.
- W3100194670 created "2020-11-23" @default.
- W3100194670 creator A5070285169 @default.
- W3100194670 creator A5090626270 @default.
- W3100194670 date "2019-08-19" @default.
- W3100194670 modified "2023-09-24" @default.
- W3100194670 title "Machine Learning on data with sPlot background subtraction" @default.
- W3100194670 cites W1503054655 @default.
- W3100194670 cites W2004388181 @default.
- W3100194670 cites W2125621954 @default.
- W3100194670 cites W2743218360 @default.
- W3100194670 doi "https://doi.org/10.1088/1748-0221/14/08/p08020" @default.
- W3100194670 hasPublicationYear "2019" @default.
- W3100194670 type Work @default.
- W3100194670 sameAs 3100194670 @default.
- W3100194670 citedByCount "8" @default.
- W3100194670 countsByYear W31001946702020 @default.
- W3100194670 countsByYear W31001946702021 @default.
- W3100194670 countsByYear W31001946702022 @default.
- W3100194670 countsByYear W31001946702023 @default.
- W3100194670 crossrefType "journal-article" @default.
- W3100194670 hasAuthorship W3100194670A5070285169 @default.
- W3100194670 hasAuthorship W3100194670A5090626270 @default.
- W3100194670 hasBestOaLocation W31001946702 @default.
- W3100194670 hasConcept C105795698 @default.
- W3100194670 hasConcept C11413529 @default.
- W3100194670 hasConcept C119857082 @default.
- W3100194670 hasConcept C121332964 @default.
- W3100194670 hasConcept C138885662 @default.
- W3100194670 hasConcept C14036430 @default.
- W3100194670 hasConcept C153180895 @default.
- W3100194670 hasConcept C154945302 @default.
- W3100194670 hasConcept C160633673 @default.
- W3100194670 hasConcept C186370098 @default.
- W3100194670 hasConcept C199360897 @default.
- W3100194670 hasConcept C207390915 @default.
- W3100194670 hasConcept C2779662365 @default.
- W3100194670 hasConcept C2779843651 @default.
- W3100194670 hasConcept C32653426 @default.
- W3100194670 hasConcept C32848918 @default.
- W3100194670 hasConcept C33923547 @default.
- W3100194670 hasConcept C41008148 @default.
- W3100194670 hasConcept C41895202 @default.
- W3100194670 hasConcept C44870925 @default.
- W3100194670 hasConcept C62520636 @default.
- W3100194670 hasConcept C68060419 @default.
- W3100194670 hasConcept C78458016 @default.
- W3100194670 hasConcept C86803240 @default.
- W3100194670 hasConcept C94375191 @default.
- W3100194670 hasConceptScore W3100194670C105795698 @default.
- W3100194670 hasConceptScore W3100194670C11413529 @default.
- W3100194670 hasConceptScore W3100194670C119857082 @default.
- W3100194670 hasConceptScore W3100194670C121332964 @default.
- W3100194670 hasConceptScore W3100194670C138885662 @default.
- W3100194670 hasConceptScore W3100194670C14036430 @default.
- W3100194670 hasConceptScore W3100194670C153180895 @default.
- W3100194670 hasConceptScore W3100194670C154945302 @default.
- W3100194670 hasConceptScore W3100194670C160633673 @default.
- W3100194670 hasConceptScore W3100194670C186370098 @default.
- W3100194670 hasConceptScore W3100194670C199360897 @default.
- W3100194670 hasConceptScore W3100194670C207390915 @default.
- W3100194670 hasConceptScore W3100194670C2779662365 @default.
- W3100194670 hasConceptScore W3100194670C2779843651 @default.
- W3100194670 hasConceptScore W3100194670C32653426 @default.
- W3100194670 hasConceptScore W3100194670C32848918 @default.
- W3100194670 hasConceptScore W3100194670C33923547 @default.
- W3100194670 hasConceptScore W3100194670C41008148 @default.
- W3100194670 hasConceptScore W3100194670C41895202 @default.
- W3100194670 hasConceptScore W3100194670C44870925 @default.
- W3100194670 hasConceptScore W3100194670C62520636 @default.
- W3100194670 hasConceptScore W3100194670C68060419 @default.
- W3100194670 hasConceptScore W3100194670C78458016 @default.
- W3100194670 hasConceptScore W3100194670C86803240 @default.
- W3100194670 hasConceptScore W3100194670C94375191 @default.
- W3100194670 hasIssue "08" @default.
- W3100194670 hasLocation W31001946701 @default.
- W3100194670 hasLocation W31001946702 @default.
- W3100194670 hasLocation W31001946703 @default.
- W3100194670 hasOpenAccess W3100194670 @default.
- W3100194670 hasPrimaryLocation W31001946701 @default.
- W3100194670 hasRelatedWork W1576493749 @default.
- W3100194670 hasRelatedWork W2008001747 @default.
- W3100194670 hasRelatedWork W2029940328 @default.
- W3100194670 hasRelatedWork W2040542981 @default.
- W3100194670 hasRelatedWork W2097491003 @default.
- W3100194670 hasRelatedWork W2101332278 @default.
- W3100194670 hasRelatedWork W2168898335 @default.
- W3100194670 hasRelatedWork W2382278161 @default.
- W3100194670 hasRelatedWork W2944436573 @default.
- W3100194670 hasRelatedWork W2981573940 @default.
- W3100194670 hasVolume "14" @default.
- W3100194670 isParatext "false" @default.
- W3100194670 isRetracted "false" @default.
- W3100194670 magId "3100194670" @default.
- W3100194670 workType "article" @default.